Intelligent capture technology behind achieving STP requires accuracy. This means examining the elements of accuracy & how to evaluate it, discussed here.
With Intelligent Capture, what gets us into trouble…is approaching document automation as an OCR problem instead of a data science problem. Find out why.
Cognitive classification is one important intelligent capture application, but it differs from other types of classification: find out how & why it matters.
One area of automation that has not done a good job of keeping-up is Intelligent Capture, find out why & how to really excel in straight through processing.
Why machine learning is not the only answer and how to find the best solution to meet your organization’s document automation needs. Find out more here.
This article delves into the key technologies involved in cognitive capture & what areas they support by looking at standard document capture workflows.
So what does 99% accuracy really mean? This article explores what 99% accuracy means for your document data extraction or document automation
Is Machine Learning all the same? Let’s delve into the most common machine learning techniques, explore how they are used and where.
New advances in handwriting recognition & data capture offer three important reasons to get a handle on & gain access to your handwritten data.
This article examines the role OCR plays in cognitive capture and how cognitive capture is used in RPA and business systems for document processing.
Are checklists useful in document automation evaluations? Here’s a checklist approach & one that requires a new approach to evaluate technology solutions.
When using advanced capture, are templates such a bad thing? This article explores the use of the “template” and when it makes sense to go “template-less.”